Need Help creating models in PyMC3 as a beginner

Hello Everyone!

I am an undergrad student, and a complete beginner to probabilistic programming in general, so I am having some problems.

For the purpose of my dissertation project, I need to evaluate the efficacy of a certain vaccine against Covid-19 using Bayesian methods. As it turns out, my population parameter (infection process, i.e., number of people infected) follows a Poisson prior, and the mean of this prior, Lambda follows a gamma distribution. The likelihood turns out to be a binomial distribution.

At the present i am trying to model the posterior distribution of Lambda. The vaccine efficacy is a function of Lambda.

Can somebody guide me as to how I can create a model in PyMC3 for this?

As an added layer of complexity, I actually have two infection processes, one for the vaccine cohort and another for the control cohort. Can I get some hint as to how to proceed for this as well?

Thank you for patiently reading and answering!!


you can go through this video and practice with the available notebook.
I found it quite useful.

All the best

Thanks!! I will definitely go through this!

Do you know of some other good, but lesser well known resources that i may use?

Hi there,
The examples on the pymc-dev repo are pretty neat. Here is the link for the repo implementing code examples from ā€˜Statistical Rethinkingā€™ textbook.

Some of the examples are explained with background - some not. Perhaps worth a (long-ish) shot at least?

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Yes will look through this definitely!!